Characterisation, Performance and Optimisation of Nanocellulose Metalworking Fluid (MWF) for Green Machining Process

2021 ◽  
Vol 18 (4) ◽  
pp. 9188-9207
Author(s):  
Mahendran Samykano ◽  
J. Kananathan ◽  
K. Kadirgama ◽  
A. K. Amirruddin ◽  
D. Ramasamy ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Alumina Nanoparticles ◽  
Working Fluid ◽  
Depth Of Cut ◽  
Nanoparticle Concentration

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour.

scholarly journals Experimental Investigation on Surface Roughness and Tool Wear in Dry Machining of TiC Reinforced Aluminium LM6 Composite

2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Dry Machining ◽  
Workpiece Surface ◽  
High Cutting Speed

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 mm.

scholarly journals Analysis and Optimization of Machining Hardened Steel AISI 4140 with Self-Propelled Rotary Tools

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6106
Author(s):  
Waleed Ahmed ◽  
Hussien Hegab ◽  
Atef Mohany ◽  
Hossam Kishawy
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Inclination Angle ◽  
Feed Rate ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Hardened Steel ◽  
Machining Process ◽  
Aisi 4140 ◽  
Steel Aisi

It is necessary to improve the machinability of difficult-to-cut materials such as hardened steel, nickel-based alloys, and titanium alloys as these materials offer superior properties such as chemical stability, corrosion resistance, and high strength to weight ratio, making them indispensable for many applications. Machining with self-propelled rotary tools (SPRT) is considered one of the promising techniques used to provide proper tool life even under dry conditions. In this work, an attempt has been performed to analyze, model, and optimize the machining process of AISI 4140 hardened steel using self-propelled rotary tools. Experimental analysis has been offered to (a) compare the fixed and rotary tools performance and (b) study the effect of the inclination angle on the surface quality and tool wear. Moreover, the current study implemented some artificial intelligence-based approaches (i.e., genetic programming and NSGA-II) to model and optimize the machining process of AISI 4140 hardened steel with self-propelled rotary tools. The feed rate, cutting velocity, and inclination angle were the selected design variables, while the tool wear, surface roughness, and material removal rate (MRR) were the studied outputs. The optimal surface roughness was obtained at a cutting speed of 240 m/min, an inclination angle of 20°, and a feed rate of 0.1 mm/rev. In addition, the minimum flank tool wear was observed at a cutting speed of 70 m/min, an inclination angle of 10°, and a feed rate of 0.15 mm/rev. Moreover, different weights have been assigned for the three studied outputs to offer different optimized solutions based on the designer’s interest (equal-weighted, finishing, and productivity scenarios). It should be stated that the findings of the current work offer valuable recommendations to select the optimized cutting conditions when machining hardened steel AISI 4140 within the selected ranges.

scholarly journals Analysis of tool wear and surface roughness in high-speed milling process of aluminum alloy Al6061

2021 ◽  
pp. 71-84
Author(s):  
Nhu-Tung Nguyen ◽  
Dung Hoang Tien ◽  
Nguyen Tien Tung ◽  
Nguyen Duc Luan
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Tool Wear ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Milling Process ◽  
Face Milling ◽  
Depth Of Cut ◽  
High Speed Milling

In this study, the influence of cutting parameters and machining time on the tool wear and surface roughness was investigated in high-speed milling process of Al6061 using face carbide inserts. Taguchi experimental matrix (L9) was chosen to design and conduct the experimental research with three input parameters (feed rate, cutting speed, and axial depth of cut). Tool wear (VB) and surface roughness (Ra) after different machining strokes (after 10, 30, and 50 machining strokes) were selected as the output parameters. In almost cases of high-speed face milling process, the most significant factor that influenced on the tool wear was cutting speed (84.94 % after 10 machining strokes, 52.13 % after 30 machining strokes, and 68.58 % after 50 machining strokes), and the most significant factors that influenced on the surface roughness were depth of cut and feed rate (70.54 % after 10 machining strokes, 43.28 % after 30 machining strokes, and 30.97 % after 50 machining strokes for depth of cut. And 22.01 % after 10 machining strokes, 44.39 % after 30 machining strokes, and 66.58 % after 50 machining strokes for feed rate). Linear regression was the most suitable regression of VB and Ra with the determination coefficients (R2) from 88.00 % to 91.99 % for VB, and from 90.24 % to 96.84 % for Ra. These regression models were successfully verified by comparison between predicted and measured results of VB and Ra. Besides, the relationship of VB, Ra, and different machining strokes was also investigated and evaluated. Tool wear, surface roughness models, and their relationship that were found in this study can be used to improve the surface quality and reduce the tool wear in the high-speed face milling of aluminum alloy Al6061

Machining Apprenticeship Based on Experimental Training Practice

2011 ◽  
Vol 692 ◽  
pp. 83-92
Author(s):  
Pedro Jose Arrazola ◽  
A. Villar ◽  
R. Fernández ◽  
J. Aperribay
Keyword(s):  
Surface Roughness ◽  
Power Consumption ◽  
Feed Rate ◽  
Cutting Forces ◽  
Theoretical Calculations ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Practical Training ◽  
Input Parameters

This article describes a practical machining training aiming that the students acquire the theoretical-practical knowledge of chip formation process. The training takes place after theoretical lessons of machining processes. Thus, this practice allows strengthening the knowledge gained during the lessons. The practical training lasts for five hours, and the student assisted by the teacher analyses the influence of some machining entry parameters (cutting speed, feed rate...) on exit parameters like: (I) cutting forces and power consumption, (II) surface roughness, and (III) chip typology. The practical session is carried out on an experimental set-up (Lathe CNC Danobar 65) equipped with sensors and devices to measure forces (sensor Kistler 9121) and power consumption. In addition, a portable rugosimeter (Hommelwerke) is employed to perform surface roughness measurements. No especial devices are needed for the chip typology analysis. In the case of cutting forces and power consumption, the following input parameters influences are analysed: feed rate, depth of cut and cutting speed. In the case of surface roughness analysis, the following input parameters influences are analysed: feed rate and nose radius of the cutting insert. Finally, regarding chip typology feed rate and depth of cut are examined. The experimental results are compared with model predictions (theoretical calculations) for the three issues studied. The students have to compare both results: theoretical an empirical and they need to explain the reasons when discrepancies appear. Results obtained during the last years demonstrate the student acquires better knowledge of the machining process, and at the same time realises of the process complexity.

Optimisation of Machining Parameters for Milling Polyetheretherketones (PEEK) Biomaterial

2014 ◽  
Vol 699 ◽  
pp. 198-203 ◽  
Author(s):  
Raja Izamshah Raja Abdullah ◽  
Aaron Yu Long ◽  
Md Ali Mohd Amran ◽  
Mohd Shahir Kasim ◽  
Abu Bakar Mohd Hadzley ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dimensional Precision ◽  
Good Surface

Polyetheretherketones (PEEK) has been widely used as biomaterial for trauma, orthopaedic and spinal implants. Component made from Polyetheretherketones generally required additional machining process for finishing which can be a problem especially to attain a good surface roughness and dimensional precision. This research attempts to optimize the machining and processing parameters (cutting speed, feed rate and depth of cut) for effectively machining Polyetheretherketones (PEEK) implant material using carbide cutting tools. Response Surface Methodology (RSM) technique was used to assess the effects of the parameters and their relations towards the surface roughness values. Based on the analysis results, the optimal machining parameters for the minimum surface roughness values were by using cutting speed of 5754 rpm, feed rate of 0.026 mm/tooth and 5.11 mm depth of cut (DOC).

An Experimental Study on Finish Dry Milling of AISI 321 Stainless Steel

2016 ◽  
Vol 861 ◽  
pp. 26-31 ◽  
Author(s):  
Peng Guo ◽  
Chuan Zhen Huang ◽  
Bin Zou ◽  
Jun Wang ◽  
Han Lian Liu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Tool Wear ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Dry Milling ◽  
Aisi 321 ◽  
Coated Cemented Carbide

The milling of AISI 321 stainless steel which has wide engineering applications particularly in automobile, aerospace and medicine is of great importance especially in the conditions where high surface quality is required. In this paper, L16 orthogonal array design of experiments was adopted to evaluate the machinability of AISI 321 stainless steel with coated cemented carbide tools under finish dry milling conditions, and the influence of cutting speed ( V ), feed rate ( f ) and depth of cut ( ap ) on cutting force, surface roughness and tool wear was analysed. The experimental results revealed that the cutting force decreased with an increase in the cutting speed and increased with an increase in the feed rate or the depth of cut. The tool wear was affected significantly by the cutting speed and the depth of cut, while the effect of the feed rate on the tool wear was insignificant. With the cutting speed increased up to 160 m/min, a decreasing tendency in the surface roughness was observed, but when the cutting speed was further increased, the surface roughness increased. The effect of the feed rate and the depth of cut on the surface roughness was slight.

scholarly journals Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

2021 ◽  
Vol 54 (2) ◽  
pp. 325-334
Author(s):  
Sampath Kumar Thepperumal ◽  
Vignesh Margabandu ◽  
Ramanujam Radhakrishnan ◽  
John Rajan Amaladas ◽  
Shri Vignesh Ananthakrishnan
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Optimal Level ◽  
Depth Of Cut ◽  
Electron Microscopic ◽  
Utility Concept ◽  
Coated Tool ◽  
Coated Carbide

In this present research, the machinability studies of TiAlN/TiCN, TiCN/TiAlN coated and uncoated inserts were investigated on machining custom 450 alloy. The machining input parameters such as feed rate (f), cutting speed (V) and depth of cut (d) are set using orthogonal array. The machining output parameters such as surface roughness, tool wear and cutting forces were studied for its parametric contribution and it was analyzed using Analysis of Variance (ANOVA). Further, the tool wear obtained was studied using scanning electron microscopic images and energy dispersive spectroscopy analysis was conducted to check the addition of work material elements to the coated tool surface. The results show that, the feed rate is the most contributing factor in deciding resultant forces, surface roughness and tool wear respectively. TiAlN/TiCN coated carbide tool has obtained improved machinability, when compared to TiCN/TiAlN coated carbide and uncoated carbide inserts. To obtain one optimal level for all three responses of three types of tools, multi criteria decision making approach, named utility concept approach is selected. Based on the MCDM analysis, it is found that trial number 4 gives better experimental output of improved surface integrity, lower resultant force and less tool wear for all types of tools.

Surface Intergrity of Inconel 718 under MQL Condition

2010 ◽  
Vol 150-151 ◽  
pp. 1667-1672 ◽  
Author(s):  
Che Hassan Che Haron ◽  
Jaharah Abd Ghani ◽  
Mohd Shahir Kasim ◽  
T.K. Soon ◽  
Gusri Akhyar Ibrahim ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Machining Process ◽  
Graphical Form ◽  
Depth Of Cut ◽  
Optimum Process ◽  
Machined Surface ◽  
Coated Carbide

The purpose of this study is to investigate the effect of turning parameters on the surface integrity of Inconel 718. The turning parameters studied were cutting speed of 90, 120, 150 m/min, feed rate of 0.15, 0.25, 0.25mm/rev and depth of cut of 0.3, 0.4, 0.5 mm under minimum quantity lubricant (MQL) using coated carbide tool. surface response methodology (RSM) design of experiment using Box-Behnken approach has been employed consisting of various combination of turning parameters Surface roughness, surface topography, microstructure and the micro hardness of the machined surface were studied after the machining process. Feed rate was found to be the most significant parameter affecting the surface roughness. The optimum parameter was obtained with Ra equal to 0.243 µm at cutting speed of 150 m/min, feed rate of 0.25 mm/rev and depth of cut of 0.3mm. A mathematical model for surface roughness was developed using Response Surface Methodology. The effect of turning parameters and factor interactions on surface roughness is presented in 3D graphical form, which helps in selecting the optimum process parameters to achieve the desired surface quality.

The Effect of Cutting Speed and Feed Rate on Surface Roughness and Tool Wear when Machining Machining D2 Steel

2017 ◽  
Vol 909 ◽  
pp. 80-85 ◽  
Author(s):  
Mohd Rasidi Ibrahim ◽  
Tharmaraj Sreedharan ◽  
Nurul Aisyah Fadhlul Hadi ◽  
Mohammad Sukri Mustapa ◽  
Al Emran Ismail ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Surface Quality ◽  
Feed Rate ◽  
Input Parameter ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
D2 Steel

Machining parameters is a main aspect in performing turning operations using lathe machines. Cutting parameters such as cutting speed, feed rate and depth of cut gives big influence on the dynamic behavior of the machining system. In machining parts, surface quality and tool wear are the most crucial customer requirements. This is because the major indication of surface quality on machined part is the surface roughness and the value of tool wear. Hence, to improve the surface roughness and minimize the forming of tool wear, the optimum feed rate and cutting speed will be determined. The input parameter such as cutting speed, feed rate and depth of cut always influence the tool wear, surface roughness, cutting force, cutting temperature, tool life and dimensional accuracy. The D2 steel was being investigated from the perspective of the effect of cutting speed and feed rate on its surface roughness and tool wear. The results show that cutting speed is the main parameter which affects the surface roughness where the most optimum parameter would be at cutting speed of 173, 231 and 288 m/min with feed rate of 0.15 mm/rev. The tool wear strongly affected by feed rate where at 0.15 mm/rev the tool wear value is the lowest. The combination of high cutting speed and low feed rate was the best parameter to achieve smooth surface roughness.

scholarly journals Influence of Cutting Fluid Flow Rate and Cutting Parameters on the Surface Roughness and Flank Wear of TiAlN Coated Tool In Turning AISI 1015 Steel Using Taguchi Method

2017 ◽  
Vol 62 (3) ◽  
pp. 1827-1832 ◽  
Author(s):  
C. Moganapriya ◽  
R. Rajasekar ◽  
K. Ponappa ◽  
R. Venkatesh ◽  
R. Karthick
Keyword(s):  
Surface Roughness ◽  
Fluid Flow ◽  
Tool Wear ◽  
Flow Rate ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Fluid Flow Rate

AbstractThis paper presents the influence of cutting parameters (Depth of cut, feed rate, spindle speed and cutting fluid flow rate) on the surface roughness and flank wear of physical vapor deposition (PVD) Cathodic arc evaporation coated TiAlN tungsten carbide cutting tool insert during CNC turning of AISI 1015 mild steel. Analysis of Variance has been applied to determine the critical influence of cutting parameters. Taguchi orthogonal test design has been employed to optimize the process parameters affecting surface roughness and tool wear. Depth of cut was found to be the most dominant factor contributing to high surface roughness (67.5%) of the inserts. However, cutting speed, feed rate and flow rate of cutting fluid showed minimal contribution to surface roughness. On the other hand, cutting speed (45.6%) and flow rate of cutting fluid (23%) were the dominant factors influencing tool wear. The optimum cutting conditions for desired surface roughness constitutes the following parameters such as medium cutting speed, low feed rate, low depth of cut and high cutting fluid flow rate. Minimal tool wear was achieved for the following process parameters such as low cutting speed, low feed rate, medium depth of cut and high cutting fluid flow rate.

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